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In this paper, we propose a method for finding the optimal route for a specific train from a station to another one in the Spanish railway network (or any railway network involving different incompatible features like gauges, electrification and signaling systems). The complexity of the Spanish railway infrastructure makes it difficult to give an estimation of the fastest route of a train from a given station to another. Indeed, very unintuitive situations may happen. The problem of finding fastest routes is typically modeled by a graph where nodes represent stations and edges represent railway sections. However, this approach is not suitable for the Spanish railway network. In order to solve the problem of calculating the fastest routes, we will propose here a novel approach based on modeling the railway network through a different graph whose nodes represent railway sections. [ABSTRACT FROM AUTHOR]

During the last two decades, the model developed by Cancelo and Espasa (1991) has been used for predicting the Spanish electricity demand with good results. This paper proposes a new approach for estimating multiequation models that extends the previous work in different and important ways. Primarily, 24-h equations are assembled to form a periodic autoregressive-moving-average model, which significantly improves the short-term predictions. To reduce the computational problem, the full model is estimated in two steps, and a meticulous model of the nonlinear temperature effect is included using regression spline techniques. The method is currently being used by the Spanish Transmission System Operator (Red Eléctrica de España , REE) to make hourly forecasts of electricity demand from one to ten days ahead. [ABSTRACT FROM AUTHOR]